DRUG SAFETY OPERATIONS IN AI ENVIRONMENT

1. Narrated Presentations
2. Reading Materials
3. Practical Quizzes & Assessments
4. AI-Augmented Role-Based Tasks
5. Case Study Exercises and Safety Scenarios

SIP – Self-Paced Online with Support

DSAI-SIP Delivery – 10 Weeks / 210 Hours (Self-Paced)

Preferred Qualifications: To excel in roles within Drug Safety, candidates should hold an associate degree for entry-level data entry positions, while a bachelor’s or master’s degree in various science-related fields is highly recommended for more advanced roles. Eligible majors for enrollment span a diverse spectrum of disciplines, including Medicine, Nursing, Pharmacy, Public Health, Chemistry, Pharmacology, Pharmaceutical Chemistry for Drug Safety Associate roles, and Medical Reviewer or Drug Safety Physician positions.

Drug Safety Associates (DSAs), Coordinators, and Specialists are essential to maintaining public health and regulatory compliance by overseeing drug safety activities throughout the lifecycle of pharmaceutical products—from clinical trials to post-marketing surveillance. The DSAI program is strategically designed to prepare learners for these roles by offering hands-on training in core pharmacovigilance functions, enhanced through artificial intelligence tools that are increasingly used in modern safety operations.

Through this program, students build practical, job-ready skills in the following areas:

Medical Record Review and Case Intake: Learn to evaluate patient histories and medical documents to identify reportable safety events and construct initial case entries.

Adverse Event Identification, Processing, and Follow-up: Gain expertise in identifying serious and non-serious adverse events (AEs and SAEs), processing them using standardized workflows, and performing required follow-ups with clinical sites and healthcare providers.

MedDRA Coding and Causality Assessments: Master the use of MedDRA (Medical Dictionary for Regulatory Activities) for accurate event classification and apply causality algorithms to determine drug-event relationships.

CIOMS, PSUR, and Signal Detection Techniques: Generate CIOMS reports, periodic safety update reports (PSURs), and utilize AI-enabled signal detection tools to recognize emerging drug safety concerns across patient populations.

SAE Reconciliation and Case Narrative Development: Learn to reconcile discrepancies between clinical trial databases and safety systems and draft comprehensive case narratives for regulatory submission.

AI-Supported Data Triage and Quality Reviews: Utilize AI for prioritizing incoming cases, flagging high-risk signals, and performing automated quality checks to improve efficiency and compliance.

Real-World Evidence (RWE) and Post-Market Surveillance:Explore post-marketing drug safety strategies, including monitoring data from electronic health records (EHRs), patient registries, and spontaneous reporting systems to ensure ongoing safety after product launch.

Throughout the program, students engage with real-world case scenarios, guided simulations, and standardized reporting templates that mirror current industry practices. By integrating AI-based automation tools with human judgment, learners develop a hybrid skill set that is in high demand across global pharmacovigilance teams

Graduates of the Drug Safety Operations in AI Environment program are well-positioned to apply for a range of entry- to mid-level roles across pharmaceutical companies, clinical research organizations (CROs), biotech firms, and regulatory service providers. Common job titles include

   Entry-Level and Associate Roles

1. Drug Safety Associate (DSA)
2. Pharmacovigilance Associate (PVA)
3. Safety Data Management Coordinator
4. Drug Safety Coordinator
5. Medical Data Reviewer
6. Case Processing Specialist

    Mid-Level Roles (with experience or advancement)

1. Signal Detection Analyst
2. Risk Management Specialist
3. Aggregate Report Specialist (CIOMS/PSUR)
4. SAE Reconciliation Specialist
5. Safety Surveillance Analyst
6. AI-Powered PV Workflow Analyst

    Specialized Roles in Tech-Enabled PV

1. MedDRA Coder / Medical Coding Specialist
2. Pharmacovigilance Systems Analyst
3. PV Automation Specialist
4. Real-World Evidence (RWE) Analyst
5. Post-Market Surveillance Coordinator

This program not only prepares students for immediate employment but also builds a strong foundation for career advancement in roles that require the integration of pharmacovigilance, data analytics, and emerging AI technologies.

   Learning Outcomes:

1. Understand regulatory frameworks and reporting timelines (e.g., FDA, EudraVigilance).
2. Perform medical data extraction, coding, and triage.
3. Apply AI in detecting adverse event patterns and signal escalation.
4. Use software for CIOMS, PSUR, and case management workflows.
5. Interpret real-world data for post-market surveillance using AI tools.

    Benefits:

1. 37+ practice hours of AI-integrated LMS training.
2. Access to Drug Safety software simulations and tools.
3. Resume Marketing Services (RMS) for job support.
4. SME support, one-on-one guidance, and mock interviews.
5. Internship and freelance job opportunities after course completion.

Upon completing the DSAI program, students gain exclusive access to Qtech-Sol’s Resume Marketing Services (RMS)—a comprehensive support system designed to accelerate job placement in AI-integrated clinical research roles.

   Our post-training assistance includes:

1. Resume and LinkedIn Profile Optimization: Tailored to highlight both traditional DSA expertise and AI-driven capabilities.
2. Narrative Development: Assistance in crafting compelling interview stories and responses aligned with real-world clinical-AI scenarios.
3. Mock Interviews: Practice sessions focused on DSA responsibilities, regulatory compliance, and AI-enabled tools.
4. Job Search Strategy & Market Insights: Personalized guidance on targeting the right roles, navigating job portals, and understanding hiring trends.
5. Direct RMS Promotion: We actively market your resume to our employer network, helping bridge the gap between training and employment.

This end-to-end support ensures you are not only trained but truly career-ready, equipped to confidently pursue roles in modern clinical research environments powered by AI.